Enterprises Of Thermal Power Coal Prices And Electricity Demand Analysis And Forecasting Of Empirical Research

Nowadays, in China's composition of energy, the thermal power takes up the predominant position. Currently, society has a high demand for electric power. But as the main fuel of the thermal power factory, there is tight supply of coal. The cost of fuel for the thermal power companies accounts for 75% of the total, which constitutes the core cost of the power stations. Under the environment of competition and coal price marketization, the thermal power companies should adopt the way which includes both prediction and planning instead of only planning. This is also the same for purchasing of coal. For companies facing up to different condition, should make prediction from both quantitative and qualitative analysis, draw up reasonable purchasing strategy, and make effective stock management. We notice that SPSS has great advantage in the statistical analysis of demand and prediction. So that we can offer help companies to get competitive advantage, reduce risk, save cost and increase the economic benefit, get higher profit. This paper uses SPSS software to make time series analysis, including time trend extrapolation, exponential smoothing and auto regression, to predict the electric power market demand and price of the coal. We can get scientific conclusion through setting up model and test. At the same time, this study also is of great positive importance and practical value for both specific thermal power company and other related companies to make similar research.